A control system generally includes a controller and a plant (e.g., motor driving a load) to be controlled which is connected to the controller through a feedback loop. In operation, the plant is controlled by the output of the controller and the plant output is fed back via a feedback path where it is subtracted from a reference input to form an error signal. This error signal is processed by the controller to generate a modified control input to the plant. The controller needs tuning to maintain an optimization of command response, disturbance rejection, stability, and noise susceptibility in the presence of changes in characteristic properties such as motor/load inertia, resonance due to a compliance, backlash and friction etc.
A controller usually includes filters and control laws. Control laws amplify error signals and add feed-forward terms to create command signals. Control laws such as PID (Proportional-Integral-Derivative) control laws are widely used because of their general purpose design. As used herein, the term a PID type control laws encompasses all variations and combinations of the PID compensator, including P, PI and PD configurations. A PID type control law is so named because its control output is derived from a weighted sum of a term proportional the input, another proportional to the integral of the input, and another proportional the derivative of the input. The PID type control law controls in a proportional control mode, integral control mode, and differential control mode simultaneously so that the system reaches a target value in a stable state within as fast a period of time as is possible. Such control laws include a proportional amplification unit with a proportional gain parameter KP, an integration unit with an integration gain parameter KI and a derivative unit with a derivative gain parameter KD.
Tuning a control law is the process of setting or adjusting the control law gains (e.g., KP, KI, KD) of the control law to achieve desired performance. For example, since the stability of a motion controller may vary due to the interaction with load condition, gains of the control law must be tuned (i.e., adjusted) regularly to operate effectively in a specific application of the controller. Control laws that are poorly tuned either act too aggressively or too sluggishly, or with insufficient margins of stability. When the uncertainty in the disturbance or process dynamic characteristics is large, the tuning of a control law is often difficult. As a result, the tuning process in the past has usually required a highly experienced technician who tuned the system manually. However, while manual tuning of a controller is possible, it is often tedious and results are often non-optimal
A Dynamic Signal Analyzer (DSA) is commonly used to perform a frequency response analysis which can provide a frequency domain tuning The DSA generates a multi-frequency signal which can be injected into the control system as a command. The response to the injected signal is returned to the DSA and analyzed often employing a Bode-Plot. A DSA unit, however, is relatively expensive. Moreover, the number of points available to the DSA for injecting test signals is often fewer than desired. As a result, the use of such equipment is usually limited to the research laboratory and is not generally available at the user site.